[Purpose/Significance] Ethnography is a rigorous field of study that is favored by researchers in the field of library and information science (LIS) due to its ability to obtain valuable first-hand data. Some LIS scholars have recognized the significance of using ethnography as a research method, and it is necessary to review the application and development of ethnography in LIS research. [Method/Process] This paper collected data from CNKI and Web of Science Core Collection. By searching and screening data, a total of 69 empirical research articles (written in both Chinese and English) that utilized ethnography as a methodology in LIS field were identified. Subsequently, this paper used content analysis to systematically review the application scenarios, methodological expansions, application paths, and misuses of ethnography in LIS research. [Results/Conclusions] Ethnography can be applied to various application scenarios in LIS research. It is commonly used to address research questions in six research topics: information behavior, library construction and development, information society issues, knowledge management, information literacy, and fundamental theories and discipline construction. The research subjects encompass a broader range of information and data users. For example, information service designers and providers in libraries, intelligence agencies, information and data centers, Internet companies, government agencies, as well as socially marginalized and information-poor groups are all potential subjects that ethnography can describe. Most research typically involves fieldwork lasting six months or more. Both interview and participant observation are not only the most commonly used independent investigative methods in ethnographic research but also frequently employed in combination as a mixed-method approach. With the application and development of ethnographic approaches, new ethnographic types suitable for different contexts and paradigms have emerged, including autoethnography, netnography, visual ethnography, and institutional ethnography. Among them, autoethnography emphasizes reflexivity, netnography is suitable for new fields based on the network, visual ethnography responds to the demand for sensory-oriented research, and institutional ethnography focuses on addressing inequalities faced by marginalized groups. Autoethnography and netnography have become new types of ethnography that LIS scholars prefer to adopt. In specific applications, different research topics tend to use different types of ethnography. This paper not only reviews the application trends of new ethnographic types in difference research topics but also compares the differences between new types of ethnography and traditional ethnography in the practical applications. The aim is to provide application paths for applying ethnography to different research topics. Additionally, this paper also points out the misuses of ethnography in terminology usage, investigation duration, and data authenticity, aiming to enhance the understanding of ethnographic methodology by relevant scholars and promote the application and development of ethnography in LIS research.

[Purpose/Significance] Argument mining, a research hotspot in the field of computational linguistics, provides machine processable structured data for computational models of argument. Argument mining tasks are closely related to artificial intelligence (AI) technologies, such as natural language processing and knowledge representation. There are numerous systematic studies in academia and a clear technical realization route has come into being. New research results continue to emerge as a result of rich resources and rapid development and iteration of deep learning, large language models (LLMs), and other technologies. This study, which reviews the research status and progress of argument mining, can serve as a resource for future research and application development. [Method/Process] Through literature review, this paper systematically reviews the relevant research basis (including foundational techniques and semantic representation models), summarizes the related technical system in terms of task framework, influencing factors of technological complexity, and method classification, and then introduces the argument mining practice and application cases for specific fields and research objectives and makes a comparative analysis. Most importantly, the overall development and characteristics of this research field are summarized, with a focus on tracking the progress of multimedia argument mining in the context of the new AI environment. [Results/Conclusions] Relevant research has experienced the development of "machine learning - deep learning" and "text only - multimodal", and the levels of development and application of various fields vary much. Future research may focus on how to achieve multigranularity and multimodal content generalization, as well as how to promote its application and implementation in practice. Possible research directions include: 1) the use of LLMs in argument mining, because they exhibit significant benefits in downstream applications such as natural language processing and multimodal learning, and can also provide certain technical conditions for the generation of argument content; 2) the use of domain knowledge organization systems such as vocabulary, knowledge base and knowledge graph: with these systems, researchers can combine domain-specific argument mining models with rich knowledge structure, to strengthen semantic representation and organization improve the systematization and dig deeper into argument mining model research in the domain; 3) promoting the application research and practice of argument mining in more fields or across disciplines, and improving the retrieval and visualization of argument information, such as combining information retrieval methods with argument mining to build the next generation of argument search engines.

[Purpose/Significance] As a basic national strategic resource, public data plays an important role in promoting high-quality economic development, enhancing social governance, and improving government service levels. The construction of an ethics framework helps participants in public data circulation such as public data producers, managers, users, and supervisors to establish an awareness of data security and ethics and regulate their behavior before public data circulation, avoiding public data ethics issues such as privacy breaches, excessive data collection, data abuse, and digital gap. [Method/Process] Based on previous studies and existing public data policies, this study summarizes the definition of public data according to legal logic and the principle of maximization and describes the differences between public data and government data in terms of data subject, data openness, and data profitability as its characteristics. Then, combined with the typical data life cycle model, the cyclic hierarchy model of the public data life cycle was constructed. In addition, by comparing the principles of public data ethics and the principles of digital technology ethics, the focus of the principles of public data ethics was analyzed, and the principles of public data ethics were summarized from the perspectives of respect, security, and equality. Finally, taking the principles of public data ethics as the criterion and the six general stages and 17 sub-stages of the public data lifecycle model as the first and second-level indicators, the ethical risks of public data at each stage were analyzed. By referring to the research at all stages of the public data lifecycle, academic achievements of domestic and international data ethics principles, provincial public data regulations, and ethical rules were listed for participants to manage their behaviors given these risks at each stage and to build a framework of public data ethics. [Results/Conclusions] This framework helps public data participants to regulate their actions, and implement prior ethical responsibilities to anticipate, avoid, and mitigate public data ethical risks before they occur throughout the life cycle. The shortcoming of this framework is that its applicability and practicability need to be tested, which is also the direction of our next research work, so as to make the framework more accurate and practical and put it into use. Additionally, it can provide references and opportunities for scholars involved in public management and services on public data ethics to stimulate the value of public data elements, promote the digitization process of public management and services, and help achieve social equity, solve disputes, and gain sustainable development.

[Purpose/Significance] A future learning center (FLC), a ground-breaking novel education model crafted in response to the burgeoning demands of a rapidly digitized and intelligent society, will undeniably spearhead the new wave of intelligent construction in contemporary university libraries. As this evolution unfolds, libraries urgently need to clarify and solidify their roles in the meticulous construction of future learning centers. Doing so will promote vibrant knowledge exchange, robustly stimulate cross-disciplinary cooperation, and also guide and embolden libraries to proactively seize unprecedented development opportunities and to collaboratively face the emerging challenges ahead. [Method/Process] To comprehend the genesis and potential of the FLC, this research undertakes a meticulous examination of its foundational concepts, overarching objectives, inherent tasks, and structural framework. It delves deep into the libraries' pivotal role in nurturing these centers, especially through the lens of role delineation and functional metamorphosis. Gleaning insights from real-world examples such as the Beijing Institute of Technology Library and the Shanghai University of Finance and Economics Library, this investigation seeks to capture a snapshot of the current operational landscape, along with its associated tribulations and challenges. Through this way, the research hopes to chart a roadmap, offering invaluable reference and actionable guidance for libraries poised to embark on their journey of creating FLCs. [Results/Conclusions] The future learning center encompasses an intelligent learning environment that melds information services with learning and teaching support. Such spaces are poised to emerge as novel grassroots learning organizations underpinning evolution in learning techniques and the genesis of knowledge. Crafting these future learning centers necessitates a systematic approach, calling for collaboration from various stakeholders. Within this context, libraries serve dual roles as both initiators and active contributors. While libraries' involvement in developing future learning centers remains in nascent stages of growth, the core challenge lies in pioneering a human-centric model that harmoniously fuses space, resources, and services to offer students an enriched, tailored, and novel learning journey. As educational paradigms shift, libraries must capitalize on this momentum, drawing from their foundational expertise in intelligent library development, to resonate with the evolving criteria of talent development. Confronted with myriad challenges-ranging from role definition, conceptual alignment, and overcoming educational reform resistance to enhancing professional acumen and navigating spatial constraints-libraries are suggested to strategically assimilate educational assets, reconfigure spatial methodologies, and proffer intelligent solutions. They should aim at fostering students' proficiency in autonomous, participatory, and investigative learning through diverse resources. In essence, libraries should evolve into hubs for information services, focal points for student learning, and pillars for teaching assistance.

[Purpose/Significance] Taking the popular "chat robot" ChatGPT and the recently launched similar product "iFLYTEK Spark" as the research object, this paper explores their applications in the identification of online health information, and discusses their advantages and disadvantages, in order to provide reference for the large-scale pre-training language model in the field of health information identification. Based on the review of relevant literature on online health information authentication, deep learning models have been widely applied in the task of online health information authentication in recent years. With the rapid development of large pre-training language models such as ChatGPT, it is a novel idea to explore their discriminating ability in online health information. [Method/Process] Researchers selected health-related information from the most authoritative rumor-refuting websites in China, used "ChatGPT" and "iFLYTEK Spark" to verify the authenticity of the online health information, evaluated their performance, and compared their identification results with the expert identification results. The identification accuracy of ChatGPT and iFLYTEK Spark language model was 93.9% and 92.9%, respectively, and the F1 value was 0.951 and 0.946, respectively, which had a good application effect. The generated explanatory texts were more detailed and the language was relatively smooth. In terms of the length and dispersion of the explanatory text, ChatGPT is closer to that of medical experts, while iFLYTEK Spark's explanatory text is relatively long and less discrete. In terms of semantic similarity, ChatGPT and iFLYTEK Spark were almost equal in performance, and their understanding of health information was close to that of human experts to some extent. Through the analysis of typical samples, it can be seen that an AI large model cannot accurately identify news or emergency information for the time being, and the understanding of individual health propositions with complex semantics will occasionally be biased. [Results/Conclusions] The experimental results show that ChatGPT and iFLYTEK Spark have good discriminative effect in the field of online health information identification, but there are shortcomings, and manual intervention is needed to ensure the accuracy and reliability of the results. In the future, in the field of AI large model research, researchers are suggested to attach importance to the construction and application of high-quality corpora in vertical fields. In the field of online health information identification, practitioners can use models such as ChatGPT as tools to help identify and refine health information. There are also limitations in this article. For example, the amount of data involved in the test is not large enough, ChatGPT uses GPT3.5 model, and the online application time of iFLYTEK Spark language model is relatively short. In future studies, the amount of online health information can be further increased, and the updated version of an AI large model can be tested and evaluated.

[Purpose/Significance] As human beings enter an information-intensive society, massive information extensively and profoundly affects and changes people's lives, and gradually causes social problems such as information rumors and information redundancy. The Internet, as the primary channel for people to obtain information, has become the hardest hit area of information problems. Online health information has a wide range of sources and complex topics, due to its uneven quality, it is difficult for users to distinguish between true and false information, which brings great challenges to people, especially middle-aged and elderly people, in obtaining, selecting and using health information. [Methods/Process] The questionnaire survey method was used to explore the characteristics of health information needs and actual behavior interaction of middle-aged and elderly people from the cognitive perspective and the behavioral perspective, respectively. The questionnaire was conducted in two stages. In the first stage, participants were asked to answer an open-ended question, "What characteristics do you think meet your standard of good health information?" in order to collect the desired health information needs of the subjects. Then, we used the grounded theory analysis method to analyze the text of the subjects' answers to form a unified TSCA ideal health information feature framework. The second round of questionnaire survey was conducted on the basis of the first round of investigation and research, and we designed relevant questions to collect the information of subjects' actual health behavior information according to the established TSCA ideal health information feature framework. [Results/Conclusions] There are four features regarding middle-aged and elderly people's needs for desired health information: information topic, information source, information content and document attribute, that is, we construct the TSCA ideal health information feature framework for middle-aged and elderly people. In the process of actual interaction with health information, middle-aged and elderly people use various information topics and sources, but rarely obtain and use information from professional health sources. The study also found that it is necessary to strengthen the scaffolding role of document attribute in the process of actual interaction with health information among middle-aged and elderly people. In addition, two modes are discovered with regard to the desired health information needs of middle-aged and elderly people: topic and source oriented (TS) and content and attribute oriented (CA), but the desired health information needs are not consistent with the actual behavior of middle-aged and elderly people. The discovery of this difference will help to serve the design of the current health information environment and optimize the development of health information literacy education and training for middle-aged and elderly people from the perspective of information characterization.

[Purpose/Significance] Think tank reports are professional analysis and policy recommendations provided by independent research institutions, which provide decision support and an important tool for policy makers and the public to promote social progress. The purpose of think tank report summary is to provide readers with a concise and clear overview, so that they can quickly understand the main content and conclusion of the report, so as to improve the efficiency of information screening, dissemination effect and knowledge transfer. At present, there are many differences in the think tank reports, which leads to inaccurate summaries. It is urgent to improve the existing text summarization methods. This paper focuses on the characteristics of think tank reports in the context of multi-topic text summarization technology. [Method/Process] Aiming at the problem that the existing models have poor effect on the summarization of think tank reports, not only the crawler technology was used to construct a think tank report dataset, but also a report summarization method was proposed using the "combined keywords" search method.. First, a keyword extraction algorithm was used to extract the keyword information in the original text. Second, a "combined keywords" search module based on cross-attention mechanism was used to improve the model's ability to capture the topic information in the text and help improve the accuracy of the summary generated by the model. Finally, in order to avoid excessive attention to keywords while ignoring the overall information of a think tank report, a contrastive learning training method was designed in the training process. [Results/Conclusions] The experimental results show that the Rouge-1, Rouge-2 and Rouge-L values of the think tank report summarization model reached 48.23, 32.55 and 42.50, respectively. The summarization model with the "combined keywords" search method proposed in this study can effectively solve the problem of inaccurate summarization caused by multi-topic texts, and the text summarization effect of the model in the field of think tank reports is better than other similar models. In addition, ablation experiments were used to prove the effectiveness of the "combined keywords" search module and contrastive learning training. There are still some shortcomings of this paper. For example, this study does not explore the location and frequency information of keywords. In addition, we will adjust the weight of keywords according to their position, frequency and importance in the text, and further expand the think tank report summary dataset.

[Purpose/Significance] Genealogy resources are huge and precious historical and cultural heritage. However, in recent years, the value of genealogical resources has been ignored or mis-estimated by the public. The number of related research papers is small, and the practice of augmented reality (AR) application in public libraries rarely involves the public service of genealogy. The published papers and practice of knowledge service of genealogical resources are the cornerstone of this research work. The purpose of this study is to give dynamic cultural value to genealogy resources in public view by exploring the innovative mode of genealogy resources in libraries. [Method/Process] This study investigates relevant domestic literature and work practices, as well as the practice of domestic and foreign libraries using AR to carry out public knowledge services. This research is based on the characteristic genealogy literature resources of Shanghai Library, and the work is based on the digital humanities construction such as Chinese genealogy knowledge service platform, including the construction of "Chinese genealogy knowledge service platform", and the mining and sorting of genealogy information, and the construction of "human name standard database". The theoretical source of this study is that genealogy and surname culture construct each other's value, and they show the value of genealogy resources from the perspective of surname culture. Finally, this study completed the practice innovation of public knowledge service based on genealogy resources in the East Library of Shanghai Library. [Results/Conclusions] Through the practice of "AR surname wall", Shanghai Library, according to our own characteristics of knowledge popularization, provided diversified knowledge services, technology and art integration and obtained the beneficial experience. We found that the existing service is too dependent on technology and artistic effect, did not solve the problem of readers superficial reading, and there is a lack of knowledge service. Based on the practice of public knowledge service of genealogy resources and digital technology, Shanghai Library provides insights into giving cultural value to genealogy resources, has made an innovative attempt in public knowledge service, and made progress and development of the popularization of genealogy knowledge and genealogy culture. In the process of practice, a lot of useful experiences have been obtained, and some problems are still yet to be solved, which not only makes more people realize the cultural value of genealogy resources, but also helps us understand the development of library resources boosted by digital humanistic technology, and the breakthrough of some exhibition items of the East Library of Shanghai Library on traditional exhibitions.

[Purpose/Significance] At the moment of library transformation, using new information technology to solve the difficulties in traditional business and optimizing the reader experience is one of the research contents of smart libraries. We use the cloud edge system technology to design and implement the Shanghai Library mobile phone book lending system, which turns readers' mobile phones into dispersed self-help book lending devices, which is a successful attempt to grafting new technology into traditional library services to solve the difficulties in traditional services and optimize readers' experience. [Method/Process] In this paper, the technology of edge collaboration is applied to the library self-service loan business. First, starting from the problems faced by RFID self-service loan and return equipment in the public library, the prototype system is determined to change readers' mobile phones into self-service book borrowing equipment for readers, so readers do not need to use fixed loan and return machine, or queue up at rush hour. Centering on reader experience, data security and replication and promotion of new services are regarded as the design objectives of the system, to explore the integration of cloud-edge collaborative technology into the system to meet the design objectives (the characteristics of the system users, system performance and the scalability and stability of the system). According to the preset performance indicators, the paper provides detailed analysis and technology selection of the system, with an introduction of what we considered and why we chose the application of the system. Finally we achieve the purpose of reducing cost and increasing efficiency and improving readers' experience. [Results/Conclusions] Out one month after the system went online, about 12,640 books were lent out by mobile mobile phone book lending system, accounting for 10% of the total circulation. Most of them were young readers (ranging from 18 to 50 years old), which showed that the system met the design expectation and reduced the demand for self-service book lending machines in libraries to a certain extent. Through the official launch of the mobile phone borrowing system, the feasibility of the application of cloud edge collaboration technology in the library is verified. Cloud edge collaboration can meet the application scenarios of multiple branch libraries, and has better scalability and stability in the promotion and replication of services. It is better than the traditional system architecture. At the same time, it really reduces the purchase demand of the East Library of Shanghai Library for the self-service borrowing machine.